ColliderConquer/Stock-Prediction-and-Quantitative-Analysis-Based-on-Machine-Learning-Method
This project studies the intrinsic relationship between the stocks’ multiple factors and the investment value of the stocks listed in China Securities Index 800 Index through the machine method. The investment system pipeline has been implemented including data acquirement, data preprocessing, model tuning and selection based on the XGBoost boosted tree model.
This project helps individual investors in the Chinese stock market identify potentially profitable stocks. It takes historical multi-factor data for stocks listed in the China Securities Index (CSI) 800, analyzes it using machine learning, and outputs a list of the top 50 stocks most likely to rise in the next month. This is designed for retail investors looking for data-driven insights to inform their stock selection and investment strategy.
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Use this if you are a retail investor in the Chinese stock market interested in using a data-driven approach to identify top-performing stocks for monthly investment.
Not ideal if you are looking for real-time trading signals, day-trading strategies, or if your focus is on markets other than the CSI 800 in China.
Stars
92
Forks
23
Language
Python
License
MPL-2.0
Category
Last pushed
Jul 01, 2021
Commits (30d)
0
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